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awesome-copilot/skills/python-azure-iot-edge-modules/SKILL.md
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* feat(skills): add IoT edge skills and align agent/instruction docs

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* docs(skills): translate IoT edge skill content to English

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---
name: python-azure-iot-edge-modules
description: 'Build and operate Python Azure IoT Edge modules with robust messaging, deployment manifests, observability, and production readiness checks.'
---
# Python Azure IoT Edge Modules
Use this skill to design, implement, and validate Python-based IoT Edge modules for telemetry processing, local inference, protocol translation, and edge-to-cloud integration.
## When To Use
Use this skill for requests like:
- "quiero crear un modulo Python para IoT Edge"
- "como despliego modulos edge con manifest"
- "necesito filtrar/agregar telemetria antes de subirla"
- "como manejo desconexiones y reintentos en edge"
## Mandatory Docs Review
Before recommending runtime behavior or deployment decisions, review:
- https://learn.microsoft.com/azure/iot-edge/
- https://learn.microsoft.com/es-es/azure/iot-edge/
Minimum checks:
- Runtime architecture and module lifecycle.
- Supported host OS and versions.
- Deployment model and configuration flow.
- Current release/version guidance.
If documentation cannot be fetched, proceed with explicit assumptions and flag them clearly.
## Python Official References and Best Practices (Required)
Before proposing Python implementation details, consult official Python sources:
- https://www.python.org/
- https://docs.python.org/3/
- https://docs.python.org/3/reference/
- https://docs.python.org/3/library/
- references/python-official-best-practices.md
Prefer official docs over community snippets unless there is a specific compatibility reason to deviate.
## Goals
- Deliver module architecture and implementation plan that is production-focused.
- Ensure reliable edge messaging under network variability.
- Provide deployment, observability, and validation artifacts.
## Module Use Cases
- Protocol adapter (serial/Modbus/OPC-UA to IoT message format).
- Telemetry enrichment and normalization.
- Local anomaly detection or inference.
- Command orchestration and local actuator control.
## Delivery Workflow
### 1) Contract and Interfaces
Define:
- Module inputs and outputs.
- Message schema and versioning policy.
- Routes and priorities for normal vs critical telemetry.
- Desired properties used for dynamic configuration.
### 2) Runtime and Packaging
Specify:
- Python runtime version target.
- Container image strategy (base image, slim footprint, CVE hygiene).
- Resource profile (CPU/memory bounds).
- Startup and health checks.
### 3) Reliability Design
Implement and validate:
- Retries with exponential backoff and jitter.
- Graceful degradation on upstream failures.
- Local queueing strategy where needed.
- Idempotent processing for replayed messages.
### 4) Security Controls
Require:
- No plaintext secrets in code or manifest.
- Least-privilege module behavior.
- Secure transport and trusted cert chain handling.
- Traceability for command handling and state changes.
### 5) Deployment and Operations
Define:
- Environment-specific deployment manifests.
- Rollout strategy (pilot, staged, broad).
- Rollback criteria.
- SLOs and alerting conditions.
## Reuse Other Skills
When relevant, combine with:
- `azure-smart-city-iot-solution-builder` for platform-level architecture.
- `appinsights-instrumentation` for telemetry instrumentation approaches.
- `azure-resource-visualizer` for architecture diagrams and dependency mapping.
Also use `references/python-official-best-practices.md` as baseline quality criteria for module design and implementation guidance.
## Required Output
Always provide:
1. Module design brief (purpose, inputs, outputs).
2. Deployment model (image, manifest, env settings).
3. Reliability and error-handling strategy.
4. Security and operations checklist.
5. Test matrix (functional, chaos, performance, rollback).
## Output Template
1. Context and assumptions
2. Module architecture
3. Deployment and configuration
4. Reliability, security, observability
5. Validation and rollout plan
## Guardrails
- Do not recommend direct production rollout without pilot stage.
- Do not embed secrets in Dockerfiles, source, or manifests.
- Do not omit health probes, restart behavior, and rollback criteria.